Algorithmization of Bureaucratic Organizations: Using a Practice Lens to Study How Context Shapes Predictive Policing Systems

• Published date: 01 September 2021
• Author: Albert Meijer,Lukas Lorenz,Martijn Wessels
• Date: 01 September 2021
• DOI: http://doi.org/10.1111/puar.13391

Research Article

837

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Abstract: The current scientific debate on algorithms in the public sector is dominated by a focus on technology rather

than organizational patterns. This paper extends our understanding of these patterns by studying the algorithmization

of bureaucratic organizations, which is the process in which an organization rearranges its working routines around

the use of algorithms. To explore the algorithmization of bureaucratic organizations, we conducted a comparative

empirical analysis of predictive policing in Berlin (Germany) and Amsterdam (Netherlands) through in-depth

qualitative research. Our study identified two emergent patterns: the ‘algorithmic cage’ (Berlin, more hierarchical

control) and the ‘algorithmic colleague’ (Amsterdam, room for professional judgment). These patterns result from

administrative cultures and reinforce existing patterns of organization. The study highlights that two patterns of

algorithmization of government bureaucracy can be identified and that these patterns depend on dominant social

norms and interpretations rather than the technological features of algorithmic systems.

Evidence for practice

• The organizational rearrangement around the use of algorithms consists of six components: technology,

expertise, information relations, organizational structure and policy, as well as monitoring and evaluation;

• The outcome of the process of organizational rearrangement around the use of an algorithm is not

determined by the technological features but influenced by social norms and interpretations of the facilities

of algorithmic systems;

• At least two different outcomes of the algorithmization of bureaucratic organization can be identified: the

‘algorithmic cage’ (hierarchical control) and the ‘algorithmic colleague’ (room for professional judgment);

• An assessment of predictive policing requires an in-depth understanding of how the algorithm is

used in the organization since we cannot assume that the organization blindly follows the system’s

recommendations.

The promise of algorithms is a more effective

public sector based on innovative analyses of

information. This promise has been echoed

in sectors as diverse as transportation, criminal

justice, policing, education, and healthcare, and

Danaher et al. (2017, p. 1) even refer to the present

time as “an algorithmic age”. These terms mirror a

widespread belief that the introduction of these new

technologies in the public sector will result in radical

changes. As recent work in sector as diverse as social

security (Eubanks 2018), education (O’Neil 2016),

child welfare (Redden, Dencik, and Warne 2020),

and policing (Brayne 2021) shows, these changes can

contribute to effectiveness but also produce risks such

as bias, discrimination, and lack of democratic control

(Veale, van Kleek, and Binns 2018). For these reasons,

the algorithmization of the public sector demands

the attention of scholars in the field of public

administration (Andrews 2019; Busuioc 2020; Vogl

et al. 2020).

Algorithms are admired and mystified but from a more

sober perspective, they are basically encoded procedures

for performing a task (Cormen 2013; Gillespie 2014).

What makes new technologies so intriguing is that

they have the ability to rearrange social practices

(Barley 1990; Orlikowski and Scott 2008). Therefore,

we need a broader understanding “that includes not

just algorithms, but also the computational networks

in which they function, the people who design and

operate them, the data (and users) on which they

act, and the institutions that provide these services,

all connected to a broader social endeavor and

constituting part of a family of authoritative systems

for knowledge production” (Yeung 2018, p. 506).

Thus, the use of algorithms is a socio-technical

phenomenon that must be seen in context to

understand its complexity and consequences.

At the moment, the scientific debate on algorithms

in the public sector is dominated by a focus on the

Albert Meijer

Lukas Lorenz

Martijn Wessels

TNO

Algorithmization of Bureaucratic Organizations: Using a

Practice Lens to Study How Context Shapes Predictive

Policing Systems

Public Administration Review,

Vol. 81, Iss. 5, pp. 837–846. © 2021 The Authors.

Public Administration Review published by

Wiley Periodicals LLC on behalf of American

Society for Public Administration.

DOI:10.1111/puar.13391.

Utrecht University School of Governance

Albert Meijer is a Professor of Public

Management at Utrecht University, the

Netherlands. His research focuses on public

administration in an information age.

Email: al.j.meijer@uu.nl

Lukas Lorenz is a junior research at

Utrecht University, the Netherlands. His

research focuses on the relation between

algorithmsand regulation.

Email: l.c.lorenz@uu.nl

Martijn Wessels is a junior scientist

innovator at TNO in the Netherlands. His

research focuses on the use of information

and communication technologies for safety

and security.

Email: martijn.wessels@tno.nl